code: def test_convert_metric_value_to_float():
      tf_tensor_val = tf.random.uniform([], dtype=tf.float32)
      assert convert_metric_value_to_float_if_possible(
          tf_tensor_val
      ) == float(tf_tensor_val.numpy())
  
file_path: mlflow/tests/tensorflow/test_tensorflow2_metric_value_conversion_utils.py
imports: import pytest
  import tensorflow
  import mlflow
  from mlflow import tracking
  from mlflow.exceptions import INVALID_PARAMETER_VALUE, ErrorCode, MlflowException
  from mlflow.tracking.fluent import start_run
  from mlflow.tracking.metric_value_conversion_utils import convert_metric_value_to_float_if_possible
label_desc: Use image node_id 2 for calling a global function with example usage: test_convert_metric_value_to_float() without return types